/*
 * feature_matching_opencv_example.cpp
 *
 *  Created on: Mar 23, 2013
 *      Author: lcad
 */
#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"

using namespace cv;

void readme();

/** @function main */
int main( int argc, char** argv )
{
	if( argc != 3 )
	{ readme(); return -1; }

	Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
	Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );

	if( !img_1.data || !img_2.data )
	{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }

	//-- Step 1: Detect the keypoints using SURF Detector
	int minHessian = 400;

	SurfFeatureDetector detector( minHessian );

	std::vector<KeyPoint> keypoints_1, keypoints_2;

	detector.detect( img_1, keypoints_1 );
	detector.detect( img_2, keypoints_2 );

	//-- Step 2: Calculate descriptors (feature vectors)
	SurfDescriptorExtractor extractor;

	Mat descriptors_1, descriptors_2;

	extractor.compute( img_1, keypoints_1, descriptors_1 );
	extractor.compute( img_2, keypoints_2, descriptors_2 );

	//-- Step 3: Matching descriptor vectors using FLANN matcher
	FlannBasedMatcher matcher(new flann::KDTreeIndexParams(), new flann::SearchParams());

	std::vector< DMatch > matches;
	matcher.match( descriptors_1, descriptors_2, matches );

	double max_dist = 0; double min_dist = 100;

	//-- Quick calculation of max and min distances between keypoints
	for( int i = 0; i < descriptors_1.rows; i++ )
	{ double dist = matches[i].distance;
	if( dist < min_dist ) min_dist = dist;
	if( dist > max_dist ) max_dist = dist;
	}

	printf("-- Max dist : %f \n", max_dist );
	printf("-- Min dist : %f \n", min_dist );

	//-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist )
	//-- PS.- radiusMatch can also be used here.
	std::vector< DMatch > good_matches;

	for( int i = 0; i < descriptors_1.rows; i++ )
	{ if( matches[i].distance < 0.25 )
	{ good_matches.push_back( matches[i]); }
	}

	//-- Draw only "good" matches
	Mat img_matches;
	drawMatches( img_1, keypoints_1, img_2, keypoints_2,
			good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
			vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

	//-- Show detected matches
	imshow( "Good Matches", img_matches );

	for( int i = 0; i < good_matches.size(); i++ )
	{ printf( "-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }

	waitKey(0);

	return 0;
}

/** @function readme */
void readme()
{ std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }



